A comprehensive indirect method is proposed in this study to estimate the dynamic characteristics of the fundamental mode and evaluate the element stiffness of a girder bridge using a passing tractor with two identical trailers. The novelty of this study is the use of the dynamic interaction between the two identical trailers and the bridge rather than that between the truck and the bridge. One of the advantages of this is that the dynamic characteristics of trailers are easier to model and analyse. Under the proposed method, the residual acceleration of the two trailers is first used to eliminate the adverse effects of road surface roughness. The fundamental natural frequency of the bridge is obtained from the Fourier transform of the resulting signal. Next, the component corresponding to this fundamental frequency was extracted using bandpass filtering. The corresponding damping ratio and mode shape can be reconstructed through a short time Fourier transform (STFT) under the assumption that the fundamental mode shape amplitude peak is located at the midspan. Finally, the element stiffness of the bridge was evaluated using the reconstructed fundamental mode shape. In this study, the proposed method is investigated via numerical examples and performs well in different scenarios, for example, in the presence of highlevel measurement noise and low-level road surface roughness. Furthermore, the method was validated through field testing on the Li-Zi-Wan bridge in Chongqing. The extracted fundamental mode shape agrees well with that obtained using the stochastic subspace identification (SSI) method. The evaluated element stiffness matches very well with both the original design and the static deflection test results.

Indirect method to identify dynamic properties of bridge by a passing vehicle is attractive recently since it does not require pre-installed sensors on bridge. However, the extracted dynamic properties are not accurate enough to identify local damages due to road surface roughness. To overcome this issue, a method to identify mode shapes and detect local damages in a simply supported bridge by movable sensory system is proposed in this study. Instead of using passing vehicles, two stationary vehicles are adopted in this study to perform as movable sensory system. They stay stationary at two different locations on the bridge subject to ambient environmental excitation, and their vertical accelerations are collected to calculate the vertical displacement of the two contact points between vehicles and bridge. Then they move to another two locations and the same procedures are repeated. After all locations along the bridge are tested, a matrix similar to frequency response matrix can be constructed and SVD method is used to extract the mode shapes. The element stiffness is thereafter evaluated by the fundamental mode shape, which can be then used to detect local stiffness reduction in the bridge. Numerical study has been conducted to validate the proposed method, and the effect of bridge damping, vehicle damping, measurement noise, and traffic flow is investigated. Moreover, field testing was conducted on Li-Zi-Wan Bridge and the results showed that the proposed method can re-construct the mode shapes and evaluate element bending stiffness as accurately as conventional direct approach. The proposed method is convenient and easy to implement in practice; and it is more robust because it is not affected by road surface roughness.

The indirect method of using a passing vehicle to identify modal properties of a girder bridge has become attractive recently. Compared to the direct method, which requires a lot of sensors installed directly on the bridge itself, the indirect method only requires a single sensor installed on the vehicle to indirectly measure the response of the bridge. However, it is difficult to eliminate the adverse effect of road surface roughness. An indirect approach based on blind source separation is proposed for the first time in this study to identify the bridge element stiffness where two movable vehicles are used. Two identical vehicles stay at rest at the designated measurement points and their vertical accelerations are collected. After one measurement, the two vehicles move to other designated measurement points and the accelerations are collected again. The same procedure is repeated until the two vehicles have moved over all the designated measurement points. Then the blind source separation technique is employed to extract the fundamental mode shape of the bridge and the improved direct stiffness method is adopted to estimate the bridge element stiffness based on the collected data, which are used to monitor the health of the bridge structure and to maintain structure safety and natural symmetry. The proposed method only requires the output response of the vehicle due to the involvement of the blind separation technique. In addition, the proposed method can overcome the adverse effect of road surface roughness because the vehicles only move between two measurements and they stay at rest during one measurement. Numerical simulation was conducted to validate the proposed method, and the effect of various factors such as bridge damping ratio and measurement noise was investigated. Field measurement on Min-Xie bridge in Chongqing city was also carried out to further investigate the feasibility of the proposed method and showed that it can perform well in extracting the fundamental mode shape and evaluating bridge element stiffness.

A damping ratio identification method of the simply supported beam based on the vehicle bridge coupling dynamics theory is proposed. Firstly, the test vehicle is designed as a single degree of freedom system according to the dynamic theory, and then the signal of the simply supported beam bridge response is obtained from the response signal of the contact point between the test vehicle and the simply supported bridge by using the sensor installed on the test vehicle. The signal including the first-order frequency of the simply supported beam bridge is filtered based on the principle of vehicle bridge coupling dynamics. Finally, the damping ratio of the simply supported beam bridge is assumed, The assumed first-order vibration mode of the simply supported beam bridge is obtained through the assumed damping ratio of the simply supported beam bridge, and the cycle is continued until the maximum value point of the first-order vibration mode calculated under the assumed damping ratio is in the middle, that is the identified real damping ratio of the simply supported beam bridge. This paper first explains the feasibility of this method from the theoretical derivation of vehicle bridge coupling dynamics, and then analyzes the vehicle bridge coupling dynamics model under the influence of different vehicle speed and unsteady vehicle speed, road roughness, environmental noise and other factors. Finally, it is preliminarily verified by real bridge test. The results show that this method can overcome the influence of external adverse factors to a certain extent, achieve the purpose of identifying the damping ratio of beam bridge, and provide a better method for identifying the damping ratio of simply supported beam bridge. It has the advantages of less parameter setting, simple and convenient operation and higher test accuracy, At the same time, it is helpful to promote the practical engineering application of the vehicle bridge coupling dynamics theory and technology based on vehicle bridge coupling in beam bridge modal parameter identification.

基于移动车辆在桥梁上运行来测试桥梁基频的间接量测法已经获得实桥的验证,提出一种新型间接量测法,该方法有别于牵引车拖动测试车辆一直运行并同步采集信号的传统间接量测方式,需牵引车同时拖动固定间距的前、后2辆测试车辆前行,并在固定点静止采集少许时间后,继续重复操作至测试车辆通行整跨桥梁,利用测试车辆上采集的信号,计算整跨桥梁的传递率矩阵,然后利用奇异值分解识别出桥梁的第1阶模态,进而利用改进的直接刚度法计算桥梁单元弯曲刚度,并进行损伤识别.首先从理论上说明该方法的可行性,然后在各类影响因素下进行数值模拟分析,最后通过某实桥试验进行初步验证.研究结果表明:相比于常规在桥梁上直接测试的方法,提出方法耗时短,机动性好,适用于大面积大区域桥梁集群快速测试;相比于传统间接量测方式,提出方法通行时间虽有少量增加,但能较好解决桥梁阻尼比、测试车阻尼、外激励变化、噪音、桥面粗糙度等传统间接量测方法中存在的问题.